AI AI Engineer: AI System Design and Ethics

Question 1

What is 'algorithmic bias' in AI systems?

Accepted Answer

Systematic and unfair discrimination in AI outputs caused by biased training data or model design

Answer

Algorithmic bias occurs when an AI system produces systematically unfair outcomes for certain groups, often reflecting historical biases in training data.

Question 2

Which principle of responsible AI ensures that stakeholders can understand and interrogate how an AI system makes decisions?

Accepted Answer

Explainability and transparency

Answer

Explainability means AI decisions can be understood by humans, while transparency ensures the system's design, data, and limitations are disclosed.

Question 3

What is 'differential privacy' in the context of AI and data science?

Accepted Answer

A mathematical framework that adds noise to data or computations to protect individual privacy while enabling aggregate analysis

Answer

Differential privacy provides mathematical guarantees that an individual's data cannot be inferred from model outputs by injecting carefully calibrated noise.

Question 4

In AI system design, what is the purpose of a 'human-in-the-loop' mechanism?

Accepted Answer

To include human oversight and intervention in AI decision pipelines for critical or uncertain cases

Answer

Human-in-the-loop keeps humans involved in reviewing, correcting, or approving AI decisions, especially where errors have high stakes.

Question 5

What is 'model cards' documentation in responsible AI?

Accepted Answer

Structured documents reporting a model's intended uses, performance across subgroups, limitations, and ethical considerations

Answer

Model cards, introduced by Google, standardize transparency by documenting a model's purpose, performance benchmarks, fairness evaluations, and known limitations.

AI - Engineer Practice Test

AI - Engineer Practice Test

AI AI Engineer: AI System Design and Ethics